AI solutions
Chatbots, copilots, and automations that quietly pay for themselves.
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sources: kb.search(question, { topK: 5 }),
cite: true,
});Off-the-shelf isn't built for you.
AI is easy to demo and hard to make useful. Most projects stall as impressive prototypes that never touch real work. We focus on the boring, valuable cases, answering the same question for the hundredth time, drafting the repetitive doc, triaging the inbox, and ship them into your actual workflow with guardrails you can trust.
Three principles.
No exceptions.
Start where it pays
We pick the task that's costing you time today, not the flashiest demo. Value first.
Grounded in your data
Answers come from your documents and systems, with sources, not confident guesses.
Guardrails + oversight
Limits, review steps, and logging so you can trust what it does and see what it did.
What you get.
In writing, by week one.
Use-case scoping
A clear, ranked list of where AI actually helps you.
Working assistant
A chatbot, copilot, or automation live in your workflow.
Integration
Connected to your docs, tools, and data.
Monitoring + tuning
Logging and adjustment so quality holds up over time.
AI chatbots and automations that do real work.
The useful cases are rarely the flashy ones. These are the ones we build.
Customer-facing assistants
A chat that answers product and service questions from your own catalog and policies, like the Claude-powered sleep expert on LA Mattress.
Internal copilots
Answers from your documents, SOPs and past tickets for staff, with sources so they can check.
Inbox and lead triage
Incoming emails, forms and messages sorted, summarised and routed, with a human approving anything that matters.
Document drafting
Quotes, reports and replies drafted from your templates and data, then reviewed by your team.
Data extraction
Structured data pulled from PDFs, emails and web pages into your systems.
Guided decisions
Quizzes and advisors that narrow a big catalog or a complex service to the right choice.
AI agents: when a chatbot isn't enough.
A chatbot answers. An agent also acts: it looks things up across your systems and takes the next step, inside limits you set.
Lead follow-up
Replies to a new enquiry within minutes, asks the qualifying questions, and books the call or hands off to a person.
Operations agents
Checks orders, schedules or inventory across the tools you use and flags or fixes the exceptions, with a log of every action.
Research and reporting
Gathers data from your systems and the web on a schedule and drafts the weekly report for someone to review.
How we keep AI honest.
An assistant that makes things up is worse than none. We ground answers in your own content (retrieval over your documents, catalog or database), show sources where it helps, and give it clear limits on what it may answer and do.
Anything with consequences gets a review step: a draft for a person to approve, a confidence threshold that hands off to a human, and logs of what it did. We measure quality on real questions before launch and keep tuning after it.
We use whichever models fit the job and your privacy needs, Anthropic, OpenAI or open-source, and design so you can switch later without rebuilding.
A good first AI project is…
- A task your team repeats many times a week
- Answerable from documents or data you already have
- Safe to have a person review before it reaches a customer
- Measurable: time saved, tickets deflected, leads answered faster
- Small enough to ship in weeks, not quarters
- Something you'd keep even if the demo wasn't impressive
The honest answers.
We ground answers in your own documents and data, with sources, and add guardrails so it stays in its lane.
Ready to start?
30-minute discovery call. No deck, no sales script. Bring the problem and we'll bring the questions.
Book a discovery call